def to_swan(
self,
filename,
append=False,
id="Created by wavespectra",
unique_times=False,
dircap_270=False,
):
"""Write spectra in SWAN ASCII format.
Args:
- filename (str): str, name for output SWAN ASCII file.
- append (bool): if True append to existing filename.
- id (str): used for header in output file.
- unique_times (bool): if True, only last time is taken from
duplicate indices.
- dircap_270 (bool): if True, ensure directions do not exceed 270 degrees
as requerid for swan to prescribe boundaries.
Note:
- Only datasets with lat/lon coordinates are currently supported.
- Extra dimensions other than time, site, lon, lat, freq, dim not yet
supported.
- Only 2D spectra E(f,d) are currently supported.
"""
# If grid reshape into site, otherwise ensure there is site dim to iterate over
dset = self._check_and_stack_dims()
# When prescribing bnds, SWAN doesn't like dir>270
if dircap_270:
direc = dset[attrs.DIRNAME].values
direc[direc > 270] = direc[direc > 270] - 360
dset = dset.update({attrs.DIRNAME: direc}).sortby("dir", ascending=False)
darray = dset[attrs.SPECNAME]
is_time = attrs.TIMENAME in darray.dims
# Instantiate swan object
try:
x = dset.lon.values
y = dset.lat.values
except NotImplementedError(
"lon/lat not found in dset, cannot dump SWAN file without locations"
):
raise
sfile = SwanSpecFile(
filename,
freqs=darray.freq,
dirs=darray.dir,
time=is_time,
x=x,
y=y,
append=append,
id=id,
)
# Dump each timestep
if is_time:
for t in darray.time:
darrout = darray.sel(time=t, method="nearest")
if darrout.time.size == 1:
sfile.write_spectra(
darrout.transpose(
attrs.SITENAME, attrs.FREQNAME, attrs.DIRNAME
).values,
time=to_datetime(t.values),
)
elif unique_times:
sfile.write_spectra(
darrout.isel(time=-1)
.transpose(attrs.SITENAME, attrs.FREQNAME, attrs.DIRNAME)
.values,
time=to_datetime(t.values),
)
else:
for it, tt in enumerate(darrout.time):
sfile.write_spectra(
darrout.isel(time=it)
.transpose(attrs.SITENAME, attrs.FREQNAME, attrs.DIRNAME)
.values,
time=to_datetime(t.values),
)
else:
sfile.write_spectra(
darray.transpose(attrs.SITENAME, attrs.FREQNAME, attrs.DIRNAME).values
)
sfile.close()
def to_swan(
self,
filename,
append=False,
id="Created by wavespectra",
ntime=None
):
"""Write spectra in SWAN ASCII format.
Args:
- filename (str): str, name for output SWAN ASCII file.
- append (bool): if True append to existing filename.
- id (str): used for header in output file.
- ntime (int, None): number of times to load into memory before dumping output
file if full dataset does not fit into memory, choose None to load all times.
Note:
- Only datasets with lat/lon coordinates are currently supported.
- Extra dimensions other than time, site, lon, lat, freq, dim not yet
supported.
- Only 2D spectra E(f,d) are currently supported.
- ntime=None optimises speed as the dataset is loaded into memory however the
dataset may not fit into memory in which case a smaller number of times may
be prescribed.
"""
# If grid reshape into site, otherwise ensure there is site dim to iterate over
dset = self._check_and_stack_dims()
ntime = min(ntime or dset.time.size, dset.time.size)
# Ensure time dimension exists
is_time = attrs.TIMENAME in dset[attrs.SPECNAME].dims
if not is_time:
dset = dset.expand_dims({attrs.TIMENAME: [None]})
times = dset[attrs.TIMENAME].values
else:
times = dset[attrs.TIMENAME].to_index().to_pydatetime()
times = [f"{t:%Y%m%d.%H%M%S}" for t in times]
# Keeping only supported dimensions
dims_to_keep = {attrs.TIMENAME, attrs.SITENAME, attrs.FREQNAME, attrs.DIRNAME}
dset = dset.drop_dims(set(dset.dims) - dims_to_keep)
# Ensure correct shape
dset = dset.transpose(attrs.TIMENAME, attrs.SITENAME, attrs.FREQNAME, attrs.DIRNAME)
# Instantiate swan object
try:
x = dset.lon.values
y = dset.lat.values
except AttributeError as err:
raise NotImplementedError(
"lon-lat variables are required to write SWAN spectra file"
) from err
sfile = SwanSpecFile(
filename,
freqs=dset.freq,
dirs=dset.dir,
time=is_time,
x=x,
y=y,
append=append,
id=id,
)
# Dump each timestep
i0 = 0
i1 = ntime
while i1 <= dset.time.size or i0 < dset.time.size:
ds = dset.isel(time=slice(i0, i1))
part_times = times[i0:i1]
i0 = i1
i1 += ntime
specarray = ds[attrs.SPECNAME].values
for itime, time in enumerate(part_times):
darrout = specarray[itime]
sfile.write_spectra(darrout, time=time)
sfile.close()
def to_swan(self,
filename,
append=False,
id='Created by wavespectra',
unique_times=False):
"""Write spectra in SWAN ASCII format.
Args:
- filename (str): str, name for output SWAN ASCII file.
- append (bool): if True append to existing filename.
- id (str): used for header in output file.
- unique_times (bool): if True, only last time is taken from
duplicate indices.
Note:
- Only datasets with lat/lon coordinates are currently supported.
- Extra dimensions other than time, site, lon, lat, freq, dim not yet
supported.
- Only 2D spectra E(f,d) are currently supported.
"""
# If grid reshape into site, otherwise ensure there is site dim to iterate over
dset = self._check_and_stack_dims()
darray = dset[attrs.SPECNAME]
is_time = attrs.TIMENAME in darray.dims
# Instantiate swan object
try:
x = dset.lon.values
y = dset.lat.values
except NotImplementedError(
'lon/lat not found in dset, cannot dump SWAN file without locations'
):
raise
sfile = SwanSpecFile(filename,
freqs=darray.freq,
dirs=darray.dir,
time=is_time,
x=x,
y=y,
append=append,
id=id)
# Dump each timestep
if is_time:
for t in darray.time:
darrout = darray.sel(time=t, method='nearest')
if darrout.time.size == 1:
sfile.write_spectra(darrout.transpose(attrs.SITENAME,
attrs.FREQNAME,
attrs.DIRNAME).values,
time=to_datetime(t.values))
elif unique_times:
sfile.write_spectra(darrout.isel(time=-1).transpose(
attrs.SITENAME, attrs.FREQNAME, attrs.DIRNAME).values,
time=to_datetime(t.values))
else:
for it, tt in enumerate(darrout.time):
sfile.write_spectra(darrout.isel(time=it).transpose(
attrs.SITENAME, attrs.FREQNAME, attrs.DIRNAME).values,
time=to_datetime(t.values))
else:
sfile.write_spectra(
darray.transpose(attrs.SITENAME, attrs.FREQNAME,
attrs.DIRNAME).values)
sfile.close()